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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

A Dynamical Systems Perspective on Nesterov Acceleration ICML 2019 A Dynamic Bayesian Network Based Merge Mechanism for Autonomous Vehicles AAAI 2019 A Family of Exact Goodness-of-Fit Tests for High-Dimensional Discrete Distributions AISTATS 2019 A Family of Robust Stochastic Operators for Reinforcement Learning NeurIPS 2019 A Fast Proximal Point Method for Computing Exact Wasserstein Distance UAI 2019 A Fast Sampling Algorithm for Maximum Inner Product Search AISTATS 2019 Affine Invariant Covariance Estimation for Heavy-Tailed Distributions COLT 2019 A Flexible Convolutional Solver for Fast Style Transfers CVPR 2019 A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations UAI 2019 A Framework for Bayesian Optimization in Embedded Subspaces ICML 2019 AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling NeurIPS 2019 A General and Adaptive Robust Loss Function CVPR 2019 A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes AISTATS 2019 A General Framework for Symmetric Property Estimation NeurIPS 2019 A Generalization Bound for Online Variational Inference ACML 2019 A General-Purpose Algorithm for Constrained Sequential Inference CoNLL 2019 A General Theory of Equivariant CNNs on Homogeneous Spaces NeurIPS 2019 A Generative Adversarial Density Estimator CVPR 2019 A Generic Acceleration Framework for Stochastic Composite Optimization NeurIPS 2019 A Generic Approach to Accelerating Belief Propagation Based Incomplete Algorithms for DCOPs via a Branch-and-Bound Technique AAAI 2019 A Genetic Algorithm for Finding a Small and Diverse Set of Recent News Stories on a Given Subject: How We Generate AAAI’s AI-Alert AAAI 2019 A Geometric Perspective on the Transferability of Adversarial Directions AISTATS 2019 A Geometry-Inspired Decision-Based Attack ICCV 2019 Aggregation Cross-Entropy for Sequence Recognition CVPR 2019 A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation NeurIPS 2019